Industry pressure to quickly adopt and install artificial intelligence (AI) systems doesn’t necessarily mean the technology is blithely coursing through enterprises. Indeed, just the opposite.
Widespread FOMO over ramming through AI initiatives has led to cries of BS from rank-and-file employees and company executives.
Two new surveys come to the painful conclusion that AI use hasn’t exactly hit the ground running at most businesses in the U.S.
A stunning 68% of 1,600 U.S. executives and knowledge workers surveyed by Writer report friction between IT and other business units, and 63% said it’s creating rifts between leadership and employees. Most tellingly, 42% of the C-suite said generative AI adoption is “fueling power struggles and tearing their company apart,” and one-third referred to GenAI as a “massive disappointment.”
“Generative AI holds transformative potential for the enterprise, but it can also create deep rifts within organizations that rely on a patchwork of point solutions or IT-built applications developed in a silo,” May Habib, CEO and co-founder of Writer, said in a statement.
Friction between business leaders and IT was particularly prickly: 71% of the C-suite admitted AI applications had created a silo within their organization. Equally troubling, although 73% of companies said they invested at least $1 million annually in GenAI, only one-third had “seen significant ROI.” Some 35% of employees said they paid out-of-pocket expenses for the GenAI tools they use because their employer didn’t provide them.
Employee retaliation is another grave concern. For reasons ranging from fear of AI to the quality of AI tools, 31% of workers, including 41% of Gen Z, admitted to “sabotaging” their company’s AI strategy, such as refusing to use AI tools or outputs.
“The companies who will lead in the next era of AI adoption are the ones putting the right processes and systems in place today,” Dan Schawbel, managing partner of Workplace Intelligence, said in a statement. “They’re prioritizing their change management efforts, cultivating support for AI among their people, and ensuring they’re making the right investment in AI tools. Above all, they’re carefully assessing AI vendors, recognizing that the right vendor is key to unlocking the full potential of AI within their business.”
Distrust of AI-related content, meanwhile, remains high among knowledge workers.
Nearly 60% of them lose trust if something “looks too perfect,” and 44% of daily AI users “do not trust any image online unless it’s flawed in some way,” according to another survey from mmhmm.
Vernon Keenan, an AI expert who works closely with Salesforce Inc., says agentic AI has had difficulty catching on with “organic uses” at enterprises because of issues with data readiness, citing recent studies from Gartner and RAND. He doesn’t expect substantive agentic AI uses to catch on until early 2026.
In an interview, Keenan points to the emergence, and importance, or what he calls Virtual Employee (VE) Economics, a theoretical framework exploring the transformative impact of AI-driven autonomous agents on organizational economics, firm dynamics and labor markets. It integrates classic economic theories of transaction costs, scale economies and organizational learning with modern AI implications.
